Update ConeML profile for 810M release
Browse files
README.md
CHANGED
|
@@ -4,7 +4,7 @@ sdk: static
|
|
| 4 |
|
| 5 |
# ConeML
|
| 6 |
|
| 7 |
-
ConeML
|
| 8 |
|
| 9 |
The company works upstream of the application layer: first determining whether specialized AI is viable for a measurable workflow, then engineering and evaluating the system around that behavior.
|
| 10 |
|
|
@@ -12,7 +12,7 @@ The company works upstream of the application layer: first determining whether s
|
|
| 12 |
|
| 13 |
- Domain-model feasibility and capability analysis
|
| 14 |
- Corpus and curriculum engineering
|
| 15 |
-
-
|
| 16 |
- Held-out, machine-verified, and calibration-focused evaluation
|
| 17 |
- Regression testing, maintenance, and system evolution
|
| 18 |
|
|
@@ -20,15 +20,16 @@ The company works upstream of the application layer: first determining whether s
|
|
| 20 |
|
| 21 |
ConeML's public model releases are research artifacts that make measured capability movement and failure boundaries inspectable. The models are evidence; the engineering methodology is the differentiator.
|
| 22 |
|
| 23 |
-
###
|
| 24 |
|
| 25 |
-
|
| 26 |
|
| 27 |
-
- [ConeML
|
| 28 |
-
- [
|
|
|
|
| 29 |
- [Public release lineage](https://coneml.com/research/)
|
| 30 |
|
| 31 |
-
Public research models are released for non-commercial use under CC BY-NC 4.0 unless stated otherwise.
|
| 32 |
|
| 33 |
## ConeML
|
| 34 |
|
|
|
|
| 4 |
|
| 5 |
# ConeML
|
| 6 |
|
| 7 |
+
ConeML is an independent model lab developing language models and training methodology focused on capability engineering, corpus design, curriculum design, activation, and evaluation.
|
| 8 |
|
| 9 |
The company works upstream of the application layer: first determining whether specialized AI is viable for a measurable workflow, then engineering and evaluating the system around that behavior.
|
| 10 |
|
|
|
|
| 12 |
|
| 13 |
- Domain-model feasibility and capability analysis
|
| 14 |
- Corpus and curriculum engineering
|
| 15 |
+
- Model training and adaptation
|
| 16 |
- Held-out, machine-verified, and calibration-focused evaluation
|
| 17 |
- Regression testing, maintenance, and system evolution
|
| 18 |
|
|
|
|
| 20 |
|
| 21 |
ConeML's public model releases are research artifacts that make measured capability movement and failure boundaries inspectable. The models are evidence; the engineering methodology is the differentiator.
|
| 22 |
|
| 23 |
+
### Latest Release: ConeML 810M Alpha Family
|
| 24 |
|
| 25 |
+
The fourth public ConeML model introduces a scratch-trained 810M family with an 8,192-token context. ConeML 810M Alpha favors executed single-function writing and two-step tasks; ConeML 810M Alpha-Arithmetic records a stronger four-lane arithmetic profile. Both ship as Hugging Face weights plus F16 and tested Q8_0 GGUFs.
|
| 26 |
|
| 27 |
+
- [ConeML 810M Alpha](https://huggingface.co/ConeML/coneml-810m-alpha)
|
| 28 |
+
- [ConeML 810M Alpha-Arithmetic](https://huggingface.co/ConeML/coneml-810m-alpha-arithmetic)
|
| 29 |
+
- [810M release analysis](https://coneml.com/research/coneml-810m-alpha/)
|
| 30 |
- [Public release lineage](https://coneml.com/research/)
|
| 31 |
|
| 32 |
+
The model cards publish task-family-matched strengths beside weak GSM8K and HumanEval results, peer wins, resource assumptions, and known limitations. Public research models are released for non-commercial use under CC BY-NC 4.0 unless stated otherwise.
|
| 33 |
|
| 34 |
## ConeML
|
| 35 |
|